Zobrazeno 1 - 10
of 177
pro vyhledávání: '"Rachid Saadane"'
Autor:
Younes Ledmaoui, Asmaa El Fahli, Adila El Maghraoui, Abderahmane Hamdouchi, Mohamed El Aroussi, Rachid Saadane, Ahmed Chebak
Publikováno v:
Computers, Vol 13, Iss 9, p 235 (2024)
This paper presents a comprehensive and comparative study of solar energy forecasting in Morocco, utilizing four machine learning algorithms: Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), recurrent neural networks (RNNs), and
Externí odkaz:
https://doaj.org/article/ce8e817b99eb41b7925acf539acf563d
Autor:
Younes Ledmaoui, Adila El Maghraoui, Mohamed El Aroussi, Rachid Saadane, Ahmed Chebak, Abdellah Chehri
Publikováno v:
Energy Reports, Vol 10, Iss , Pp 1004-1012 (2023)
The use of solar energy has been rapidly expanding as a clean and renewable energy source, with the installation of photovoltaic panels on homes, businesses, and large-scale solar farms. The increasing demand for sustainable energy sources has pushed
Externí odkaz:
https://doaj.org/article/21bcb2787f904885b45e644a8838fa7b
Publikováno v:
Sensors, Vol 24, Iss 4, p 1230 (2024)
This study provides a comprehensive analysis of the combination of Genetic Algorithms (GA) and XGBoost, a well-known machine-learning model. The primary emphasis lies in hyperparameter optimization for fraud detection in smart grid applications. The
Externí odkaz:
https://doaj.org/article/8c13450b20bc42799e7fa182b4a0d913
Autor:
Hanae Belmajdoub, Khalid Minaoui, Anass El Aouni, Karim Hilmi, Rachid Saadane, Abdellah Chehri
Publikováno v:
Remote Sensing, Vol 15, Iss 14, p 3459 (2023)
Being a component of the Eastern Boundary Upwelling (EBU) ecosystem, Morocco’s Atlantic coast presents high biological production throughout the year, with seasonal variations in upwelling dynamics. This characterization reflects the inherent natur
Externí odkaz:
https://doaj.org/article/6f1ae477c78442498e63674121e06fee
Publikováno v:
Journal of Sensor and Actuator Networks, Vol 12, Iss 1, p 16 (2023)
Device-to-device (D2D) communication will play a meaningful role in future wireless networks and standards, since it ensures ultra-low latency for communication among near devices. D2D transmissions can take place together with the actual cellular co
Externí odkaz:
https://doaj.org/article/4fba46cdbd6c45b797defcefd144dabb
Publikováno v:
Materials, Vol 16, Iss 2, p 753 (2023)
Selective laser sintering (SLS) is one of the key additive manufacturing technologies that can build any complex three-dimensional structure without the use of any special tools. Thermal modeling of this process is required to anticipate the quality
Externí odkaz:
https://doaj.org/article/6aab88f36db74da79d01e73097aad7dd
Autor:
Oumaima Moutik, Hiba Sekkat, Smail Tigani, Abdellah Chehri, Rachid Saadane, Taha Ait Tchakoucht, Anand Paul
Publikováno v:
Sensors, Vol 23, Iss 2, p 734 (2023)
Understanding actions in videos remains a significant challenge in computer vision, which has been the subject of several pieces of research in the last decades. Convolutional neural networks (CNN) are a significant component of this topic and play a
Externí odkaz:
https://doaj.org/article/1626074ba0e84536a31618196fee0b0e
Autor:
Hajar Zoubir, Mustapha Rguig, Mohamed El Aroussi, Abdellah Chehri, Rachid Saadane, Gwanggil Jeon
Publikováno v:
Remote Sensing, Vol 14, Iss 19, p 4882 (2022)
Conventional practices of bridge visual inspection present several limitations, including a tedious process of analyzing images manually to identify potential damages. Vision-based techniques, particularly Deep Convolutional Neural Networks, have bee
Externí odkaz:
https://doaj.org/article/1e0cabb818d5494e9a1ab9d80230a589
Publikováno v:
Agriculture, Vol 12, Iss 3, p 329 (2022)
Smart agriculture today uses a wide range of wireless communication technologies. Low Power Consumption Embedded Devices (LPCED), such as the Internet of Things (IoT) and Wireless Sensor Networks, make it possible to work over great distances at a re
Externí odkaz:
https://doaj.org/article/848f05497a1f42ce9431d77f9460c6f5
Publikováno v:
Applied Sciences, Vol 11, Iss 17, p 7917 (2021)
While working side-by-side, humans and robots complete each other nowadays, and we may say that they work hand in hand. This study aims to evolve the grasping task by reaching the intended object based on deep reinforcement learning. Thereby, in this
Externí odkaz:
https://doaj.org/article/bd1f579606d34d51ac16ba7f19428c81